Even as a chemistry student, I've always been fascinated by vibrational spectroscopy, by the way light interacts with molecular vibrations, and by the amount of information that can be gathered from it. During my career in science, I used Raman spectroscopy, together with its variants known as Resonance Raman and SERS (Surface-Enhanced Raman Spectroscopy), to investigate a variety of systems of increasing chemical complexity: from simple molecules to proteins, cells, tissues and even living organisms. 
The need for metal nanoparticles or, in general, nanostructured metal surfaces as substrates for SERS sparkled my interest for nanotechnology, and for the way such nanostructures interact with biomolecules and with increasingly complex biological systems.
Last but not least, the complexity of such systems, and the wealth of information hidden therein, drove me to using chemometrics as a tool to extract the information I needed.

More recently, my research interests focus in particular on the three topics described below.

SERS-based biofluids analysis

Tags: SERS, nanoparticles, blood, serum, urine, diagnosis, therapeutic drug monitoring, cancer
Biofluids such as blood or urine are rich in information about our health status. Because of their biochemical complexity, however, such an information is not always easily accessed. In traditional blood and urine tests, only a fraction of such information is obtained, after time-consuming and costly processing and various instrumental analyses.
Nanotechnology, and in particular gold and silver nanostructures, when combined with optical spectroscopy, might be the key to rapidly get useful information from small volumes of biofluids (e.g. a drop of blood). In SERS (Surface-Enhanced Raman Spectroscopy), biofluids are put in contact with metal nanostructures and illuminated by a laser. In few seconds, the light scattered by the sample is analyzed and gives information about its chemical composition.
Together with my collegues and with the collaboration of the clinicians at the National Cancer Institute (CRO) of Aviano (Pordenone, Italy), I aim at developing SERS-based methods to meet some urgent needs in clinical oncology, such as the early detection and screening of aggressive cancers, or the therapeutic monitoring of anti-cancer drugs, so to minimize their heavy side effects while maximizing their efficacy.

Selected publications:

Bonifacio, A., Cervo, S., Sergo V.
(2015) Analytical and Bioanalytical Chemistry, Article in Press. 

Del Mistro, G., Cervo, S., Mansutti, E., Spizzo, R., Colombatti, A., Belmonte, P., Zucconelli, R., Steffan, A., Sergo, V., Bonifacio, A.
(2015) Analytical and Bioanalytical Chemistry,  407 (12), pp. 3271-3275.

Vicario, A., Sergo, V., Toffoli, G., Bonifacio, A.
(2015) Colloids and Surfaces B: Biointerfaces, 127, pp. 41-46.

Hyperspectral "chemical" imaging of biological tissues
Tags: chemical imaging, molecular imaging, Raman microspectroscopy, tissues, optical biopsy, diagnosis
Physicians often need to take a bit of tissue from your body (a "biopsy") to analyze it and achieve a diagnosis. Biopsies are never pleasant, and sometimes can be painful, or can lead to bleeding complications. However, there might be alternatives. An "optical biopsy" based on Raman spectroscopy only involves the illumination with a laser of the tissue to be investigated, without actually cutting and taking a sample, to get the diagnostic information. Studying biological tissues with Raman micro-spectroscopy is an important step toward the final goal of developing such an Optical Biopsy method. Upon laser illumination, and the subsequent analysis of the scattered light, the distribution of biochemical species can be "mapped", achieving what is called "chemical imaging" of a sample. The information contained by such "chemical images" can be used, for instance, to make a diagnosis, or to study the fundamental processes involved in a disease.

Selected publications:

Beleites, C., Bonifacio, A., Codrich, D., Krafft, C., Sergo, V.
(2013) Current Medicinal Chemistry, 20 (17), pp. 2176-2187.

Bonifacio, A., Beleites, C., Vittur, F., Marsich, E., Semeraro, S., Paoletti, S., Sergo, V.
(2010) Analyst, 135 (12), pp. 3193-3204. 

Bonifacio, A., Sergo, V.
(2010) Vibrational Spectroscopy, 53 (2), pp. 314-317.

Chemometrics and Spectroscopy

Tags: chemometrics, multivariate analysis, R, hyperSpec, cluster analysis, PCA, LDA, predictive models, classification

The laser light "inelastically" scattered by chemically complex samples such as tissues or biofluids (i.e. their "Raman spectrum") contains plenty of information. So much information that is actually not trivial to get the interesting bit among the mass of non-relevant data. Thus, data analysis plays a crucial role when analyzing a set of Raman spectra of biological specimen. That is why chemometrics (and in particular multivariate statistics), a set of advanced statistical techniques used to analyze complex data sets, comes into play. Although I am not a statistician (or chemometrician), I am interested in exploring how existing chemometric methods can be used to get meaningful information out of spectroscopic data. For that purpose, I use R - a free software environment for statistical computing and graphics - together with the hyperSpec, an R package dedicated to the processing of spectroscopic data developed by a friend and former collegue, Dr. Claudia Beleites.

Selected publications:

Bonifacio, A., Beleites, C., Sergo, V.
(2014) Analytical and Bioanalytical Chemistry,  407 (4), pp. 1089-1095. 

Bonifacio, A., Beleites, C., Vittur, F., Marsich, E., Semeraro, S., Paoletti, S., Sergo, V.
(2010) Analyst, 135 (12), pp. 3193-3204.